Child care quality is associated with child outcomes, but high-quality child care is rare. The goal of this project is to improve the understanding of the quantitative relationship between child outcomes and a measure of teacher-child interactions (the Classroom Assessment Scoring System, or CLASS) that is increasingly used in program improvement and in high-stakes applications such as quality rating and improvement systems and Head Start designated renewal. The study will use monotonic generalized additive models (monotonic GAM) to analyze the possibly curvilinear relationship between CLASS (and specific domains and dimensions within CLASS) and child outcomes in existing datasets available from Research Connections. The analysis plan includes specific hypotheses about curvilinear relationships between CLASS and child outcomes that will allow us to test for the presence of low thresholds for achieving strong relationships, high thresholds beyond which diminishing returns are seen, and differences in curvilinear relationships among specific domains and dimensions of the CLASS. By addressing the nature of the link between child care observation tools and child outcomes, this proposal addresses two research topics of current relevance to decision makers at local, state, and national levels: ongoing child care quality improvement and child wellbeing.